Titlebook: Data Mining in Biomedicine; Panos M. Pardalos,Vladimir L. Boginski,Alkis Vazac Book 2007 Springer-Verlag US 2007 Biomedicine.Clustering.ST

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Panos M. Pardalos,Vladimir L. Boginski,Alkis VazacDemonstrates how new data mining methodologies are successfully applied in real-life biomedical practice, which makes it attractive to both researchers and practitioners.Includes supplementary materia

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https://doi.org/10.1007/978-981-15-4350-0ataset, and show that its use allows the classification of most of the observations left unclassified by .. The accuracy of this extended . classification is compared on several publicly available benchmark datasets to that of the original . classification, and to that of the classifications provide

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https://doi.org/10.1007/978-981-15-4350-0the basis of exploration of massive data sets provided by DNA microarray probes. A number of data mining techniques have been used for such exploration to achieve the desirable results. However, high dimensionality and uncertain accuracy of microarray datasets remain the major obstacles in revealing

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Delphine Lautier,Julien Ling,Franck Raynaudtion of dissimilarity between the individual samples. In clustering microarray data, dissimilarity measures are often subjective and predefined prior to the use of clustering techniques. In this chapter, we present an ensemble method to define the dissimilarity measure through combining assignments

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Calibration of Electricity Price Modelsrimental evidence has suggested that there exists strong correlation between CpG islands and genes immediately following them. Much research has been done to identify CpG islands in a DNA sequence using various models. In this chapter, we introduce two alternative models based on high order and vari

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Adrien Nguyen Huu,Nadia Oudjanees the sub-structure discovery process from the classification model construction and uses frequent subgraph discovery algorithms to find all topological and geometric sub-structures present in the dataset. The advantage of this approach is that during classification model construction, all relevant

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